Title:
Methods for Localization and Mapping Using Vision and Inertial Sensors
Methods for Localization and Mapping Using Vision and Inertial Sensors
Author(s)
Wu, Allen D.
Johnson, Eric N.
Johnson, Eric N.
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Abstract
The problems of vision-based localization and mapping are currently highly active areas of research for
aerial systems. With a wealth of information available in each image, vision sensors allow vehicles to gather
data about their surrounding environment in addition to inferring own-ship information. However, algorithms
for processing camera images are often cumbersome for the limited computational power available onboard
many unmanned aerial systems. This paper therefore investigates a method for incorporating an inertial measurement
unit together with a monocular vision sensor to aid in the extraction of information from camera
images, and hence reduce the computational burden for this class of platforms. Feature points are detected
in each image using a Harris corner detector, and these feature measurements are statistically corresponded
across each captured image using knowledge of the vehicle's pose. The investigated methods employ an Extended
Kalman Filter framework for estimation. Real-time hardware results are presented using a baseline
configuration in which a manufactured target is used for generating salient feature points, and vehicle pose
information is provided by a high precision motion capture system for comparison purposes.
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Date Issued
2008-08
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Text
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Proceedings